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Clustering Macroeconomic Variables

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Abstract

Many papers have highlighted that some macroeconomic time series present structural instability. The causes of these remarkable changes in the reduced form properties of the macroeconomy is a debated argument. In literature this issue is handled with three main econometric methodologies: structural breaks, regime-switching and time-varying parameters (TVP). Nevertheless all these approaches need some ex ante structure in order to model the change. Based on the Recurrent Chinese Restaurant Process, I have specified a model for an autoregressive process and estimated via particle filter using a conjugate prior, which applied the idea of evolutionary cluster to the study of the instability in output and inflation for US after War World II. This procedure displays some advantages, in particular does not require a strong ex ante structure in order to neither detect the breaks nor manage the evolution of parameters. The application of the cluster procedure to GDP growth and inflation rate for US from 1957 to 2011 shows a good ability in fit the data, moreover it produces a clusterization of the time series that could be interpreted in terms of economic history and it is able to recover key data features without making restrictive assumptions, as in âone-breakâ or TVP models.

Suggested Citation

  • Chiara Perricone, 2013. "Clustering Macroeconomic Variables," CEIS Research Paper 283, Tor Vergata University, CEIS, revised 11 Jun 2013.
    • Handle: RePEc:rtv:ceisrp:283
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    JEL classification:

    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications

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